How do I use mcp-divineapi-docs?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-divineapi-docs Find documentation for the birth chart Vedic endpoint" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

mcp-divineapi-docs

by nitishautomates

Overview Schema Related Servers Score Discussions

Python

Remote

Divine API - Documentation MCP Server

A public, read-only MCP server that answers "how do I use the DivineAPI REST API". It serves the already-public developer documentation: every endpoint, its parameters, its response fields, the global auth and error rules, and real captured example responses.

This server does NOT call the astrology APIs and needs NO credentials. It is a reference, not a data source. To actually run astrology requests, use the divineapi SDK or the data MCP servers:

Indian / Vedic: https://mcp.divineapi.com/indian/mcp
Western: https://mcp.divineapi.com/western/mcp
Horoscope, Tarot and Numerology: https://mcp.divineapi.com/horoscope/mcp

Public endpoint

https://mcp.divineapi.com/docs/mcp

No API key, no auth token, no OAuth. Just connect.

Related MCP server: RootApp Documentation MCP Server

Tools (5)

Tool	What it does
`search_docs(query, limit=8)`	Case-insensitive keyword search across every endpoint card; returns the top matching cards (most query tokens first).
`get_endpoint(path)`	The full reference card for one exact path, or the closest match / a "did you mean..." list.
`list_endpoints(category="")`	Every `path [host]` line, optionally filtered to a category (Indian, Western, Numerology, PDF, Horoscope, Lifestyle, Calculators).
`get_playbook()`	The global rules: auth, error semantics per host, birth params, horoscope selectors, field formats, house systems, and what not to do.
`get_example(path)`	A real captured example response body for the path (version-agnostic slug fallback), or a pointer to the card's `returns:` line.

Data sources

docs-pack.txt is fetched live at startup from https://developers.divineapi.com/docs-pack.txt (10s timeout); on failure the server falls back to the bundled snapshot shipped in this repo.
examples.json is a map of normalized_path -> example response body, generated from the published Postman collection by build_examples.py. Regenerate it with:

python3 build_examples.py "/path/to/DivineAPI_Collection_with_examples_Final Version.json"

Run locally

python -m venv .venv && source .venv/bin/activate
pip install ".[http]"

# stdio (for Claude Desktop, Cursor, etc.)
divineapi-docs-mcp

# HTTP (streamable-http on :8000)
MCP_TRANSPORT=http uvicorn server:app --host 0.0.0.0 --port 8000

Deploy

Mirrors the DivineAPI data MCPs. The container runs uvicorn server:app on port 8000; docker-compose maps host port 8004 -> 8000.

docker compose up -d --build

Documentation: https://developers.divineapi.com

Available Tools

5 tools

get_endpointA

Return the full reference card for one endpoint path.

Give an exact path such as /indian-api/v1/auspicious-timings. If the path is not an exact match, the closest single endpoint (substring on the last path segment) is returned, otherwise a short "did you mean..." list of candidates. The card lists the host, summary, params (with * for required and example values), and the top-level response fields (returns: line).

ParametersJSON Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description fully discloses behavior: exact match returns card, substring match returns closest endpoint, no match returns did-you-mean list. It also details the card's contents (host, summary, params, response fields). No annotations are provided, but the description covers all relevant behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at four sentences, front-loaded with the main purpose, then providing examples and behavior details. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter) and the presence of an output schema (not shown but noted), the description fully covers input behavior, matching logic, and output contents. It is complete enough for an agent to understand and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'path' with no description (0% coverage). The description adds crucial meaning: provides an example path, explains how the path is matched, and clarifies the behavior for exact vs. approximate matches. This fully compensates for the schema's lack of detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a full reference card for an endpoint path, with specific verb 'Return' and resource 'reference card'. It distinguishes from siblings like get_example (examples) and list_endpoints (listing) by focusing on a single endpoint's card.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when you need a reference card for a specific endpoint path. It explains input expectations (exact path) but does not explicitly mention when not to use or list alternatives among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_exampleA

Return a real captured example response body for an endpoint path.

Uses the bundled examples (with a version-agnostic slug fallback, so an example captured at /api/v2/x also answers for /api/v3/x). If no example was captured for the path, points you to the card's returns: line instead.

ParametersJSON Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden. It reveals two key behaviors: version-agnostic matching and fallback to the 'returns: line'. It does not mention auth or rate limits, but for a read-only retrieval tool, this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each with a clear role: purpose, version behavior, failure mode. No redundancy or fluff. Excellent front-loading.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema is present (not shown), so return values need not be described. The description covers the primary function, edge cases, and key behavioral nuances. Given low complexity, it is fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'path' has 0% schema description coverage. The description references 'endpoint path' but does not specify format, examples, or constraints beyond the property name. Adding semantics like 'expected format: /api/v2/x' would improve clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Return a real captured example response body for an endpoint path,' specifying the verb and resource. It distinguishes from siblings by focusing on example retrieval rather than endpoint metadata or documentation search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the version-agnostic slug fallback and the fallback behavior when no example is captured, guiding the agent on expected outcomes. It does not explicitly contrast with siblings but provides context for when the tool succeeds or fails.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_playbookA

Return the global DivineAPI usage rules (the docs-pack header).

Covers authentication (Bearer token + api_key form field), error semantics per host, the standard birth params, horoscope selectors, field formats, house systems, SDK installs, the MCP server URLs, and a "what not to do" list of common mistakes. Read this before constructing any request.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.3/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions coverage of authentication and error semantics but does not explicitly state that the tool is read-only, non-destructive, or clarify side effects. More explicit disclosure of behavioral traits would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: a single sentence defining the main purpose, followed by a list of content areas. It is front-loaded and efficient, with no redundant or unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters, no annotations, but an existing output schema, the description provides comprehensive context about the tool's return value and its scope. It covers all necessary aspects for a zero-input tool, making it complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and 100% schema description coverage. The description adds value by explaining what the tool returns (usage rules), which goes beyond the schema. Baseline for no parameters is 4, and this is justified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool returns the global DivineAPI usage rules (the docs-pack header), listing specific content areas. This distinguishes it from siblings like get_endpoint or search_docs, which likely focus on individual endpoints or search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises 'Read this before constructing any request,' providing strong usage guidance. While it does not explicitly list when not to use or compare to alternatives, the imperative is clear and contextually sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_endpointsA

List endpoint paths with their hosts, optionally filtered by category.

With no argument, lists every endpoint as "path [host]" lines. Pass a category substring (case-insensitive) to filter, e.g. "Indian", "Western", "Numerology", "PDF", "Horoscope", "Lifestyle", or "Calculators".

ParametersJSON Schema

Name	Required	Description	Default
`category`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses output format ('path [host]' lines) and case-insensitive filtering. Lacks explanation of error handling or rate limits, but adequate for a simple listing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with main purpose. No extraneous information. Every word contributes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Has output schema so return values need not be detailed. Description covers listing and filtering. Lacks mention of pagination or limits, but tool is likely simple enough. Adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has no description for parameter 'category' (0% coverage). Description adds essential semantics: case-insensitive substring filter with concrete examples ('Indian', 'Western', etc.), greatly aiding correct parameter use.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'List', resource 'endpoint paths with hosts', and filter capability. It distinguishes from siblings like get_endpoint which retrieves a single endpoint.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: use without argument for full list, or with category substring for filtered list. Examples given. Could explicitly contrast with siblings but implication is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_docsA

Search the DivineAPI docs by keyword and return the matching endpoint cards.

Case-insensitive token scan over every endpoint reference card. Cards that match more of the query's tokens rank first. Returns up to limit whole cards (path, summary, params, returns). Use this when you know roughly what you want ("auspicious timings", "natal wheel", "love compatibility") but not the exact path.

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes case-insensitive token scan, ranking by match count, and return of entire cards with specific fields. No contradictions, and covers behavior beyond schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded purpose, efficient sentences, no fluff. Every sentence adds value: purpose, algorithm, usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given output schema and sibling tools, description is complete: explains return format, ranking, and usage. Lacks pagination info but acceptable for search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema coverage at 0%, description compensates by explaining `query` as keyword and `limit` as 'up to limit whole cards,' adding meaning beyond basic schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states verb (search), resource (docs), and outcome (return matching endpoint cards). Distinguishes from siblings like get_endpoint and list_endpoints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: 'when you know roughly what you want but not the exact path.' While no direct alternatives are named, sibling tools imply alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

5 tool updatesv1.0.0Jul 14, 2026
- First observedget_endpoint
- First observedget_example
- First observedget_playbook
- First observedlist_endpoints
- First observedsearch_docs

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.5/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: get_endpoint returns reference cards, get_example returns example responses, get_playbook returns global rules, list_endpoints lists paths, and search_docs searches by keyword. There is no overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with lowercase and underscores: get_endpoint, get_example, get_playbook, list_endpoints, search_docs. The naming is predictable and uniform.

Tool Count5/5

With 5 tools, the server is well-scoped for its purpose of serving API documentation. It provides essential functions for retrieving endpoint details, examples, listing, searching, and understanding rules without being excessive or insufficient.

Completeness5/5

The tool set covers all key documentation activities: listing endpoints, searching by keyword, retrieving detailed reference cards, accessing example responses, and obtaining usage rules. There are no obvious missing features for the domain.

Maintenance

ActivitySlowing

ResponsivenessSyncing

Resources

GitHub Repository

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